Plotting Smooth Lines with PyPlot
PyPlot offers various methods for customizing data visualizations. One common task is smoothing lines between plotted points to create a more continuous appearance. While creating smooth lines in Gnuplot is straightforward using the "smooth cplines" option, PyPlot requires a slightly different approach.
Smoothing Lines with scipy.interpolate
One solution is to employ the scipy.interpolate module. This module provides a powerful tool named spline, which can generate interpolated curves by fitting a spline function through a set of data points. Here's an example:
<code class="python">from scipy.interpolate import spline # 300 represents the number of points to generate between T.min and T.max xnew = np.linspace(T.min(), T.max(), 300) power_smooth = spline(T, power, xnew) plt.plot(xnew,power_smooth) plt.show()</code>
This code will create a smooth curve by fitting a spline through the original data points.
Deprecation of spline
Note that in scipy version 0.19.0 and later, the spline function was deprecated. To maintain compatibility, you can use the BSpline class as shown below:
<code class="python">from scipy.interpolate import make_interp_spline, BSpline # 300 represents the number of points to generate between T.min and T.max xnew = np.linspace(T.min(), T.max(), 300) spl = make_interp_spline(T, power, k=3) # type: BSpline power_smooth = spl(xnew) plt.plot(xnew, power_smooth) plt.show()</code>
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